Author: Choujun Zhan; Chi K. Tse; Zhikang Lai; Tianyong Hao; Jingjing Su
Title: Prediction of COVID-19 Spreading Profiles in South Korea, Italy and Iran by Data-Driven Coding Document date: 2020_3_10
ID: mr8z65o5_8
Snippet: where β j is the rate at which a susceptible individual is infected by an infected individual in city j, α j is the rate at which a susceptible individual is infected by an exposed individuals in city j, κ j is the rate at which an exposed individual becomes infected in city j, and γ j is the recovery rate in city j, k I is the possibility of an infected individual moving from one city to another, and δ j is the eventual percentage of the po.....
Document: where β j is the rate at which a susceptible individual is infected by an infected individual in city j, α j is the rate at which a susceptible individual is infected by an exposed individuals in city j, κ j is the rate at which an exposed individual becomes infected in city j, and γ j is the recovery rate in city j, k I is the possibility of an infected individual moving from one city to another, and δ j is the eventual percentage of the population infected in city j. Moreover, the eventual infected population in city j is given by N s j = δ j P j . To facilitate comparison and matching of profiles, we introduce the normalized states as
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